Countering active attacks on RAFT-based IoT blockchain networks

Buttar, H. M., Aman, W., Rahman, M. M. U. and Abbasi, Q. H. (2023) Countering active attacks on RAFT-based IoT blockchain networks. IEEE Sensors Journal, 23(13), pp. 14691-14699. (doi: 10.1109/JSEN.2023.3274687)

Abstract

This article considers an Internet-of-Things (IoT) blockchain wireless network consisting of a leader node and various follower nodes which together implement the reliable, replicated, redundant, and fault-tolerant (RAFT) consensus protocol to verify a blockchain transaction, as requested by a blockchain client. Furthermore, two kinds of active attacks, that is, jamming and impersonation, are considered on the IoT blockchain network due to the presence of multiple active malicious nodes in the close vicinity. When the IoT network is under a jamming attack, we utilize the stochastic geometry tool to derive the closed-form expressions for the coverage probabilities for both uplink (UL) and downlink (DL) IoT transmissions (which eventually translate to the blockchain transaction success rate). On the other hand, when the IoT network is under an impersonation attack, we propose a novel method that enables a receive IoT node to exploit the pathloss of a transmit IoT node as its fingerprint to implement a binary hypothesis test for transmit node identification. To this end, we also provide the closed-form expressions for the probabilities of false alarms, missed detection, and misclassification. Finally, we present detailed simulation results that indicate the following: 1) the coverage probability (and hence the blockchain transaction success rate) improves as the jammers’ locations move away from the IoT network and 2) the three error probabilities decrease (i.e., chances of corruption of the blockchain ledger data due to false data injection by malicious node decrease) as a function of the quality of the link between the transmit and receive IoT nodes.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer
• Authors: Buttar, H. M., Aman, W., Rahman, M. M. U., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: IEEE Sensors Journal
• Publisher: IEEE
• ISSN: 1530-437X
• ISSN (Online): 1558-1748
• Published Online: 24 May 2023
• Copyright Holders: Copyright © 2023 IEEE
• First Published: First published in IEEE Sensors Journal 23(13): 14691-14699
• Publisher Policy: Reproduced in accordance with the publisher copyright policy